A Semi-Quantitative Isothermal Diagnostic Assay Utilizing Competitive Amplification

Abstract

Quantitative diagnostics that are rapid, inexpensive, sensitive, robust, and field-deployable are needed to contain the spread of infectious diseases and inform treatment strategies. While current gold-standard techniques are highly sensitive and quantitative, they are slow and require expensive equipment. Conversely, current rapid field-deployable assays available provide essentially binary information about the presence of the target analyte, not a quantitative measure of concentration. Here, we report the development of a molecular diagnostic test [quantitative recombinase polymerase amplification (qRPA)] that utilizes competitive amplification during a recombinase polymerase amplification (RPA) assay to provide semi-quantitative information on a target nucleic acid. We demonstrate that qRPA can quantify DNA, RNA, and viral titers in HIV and COVID-19 patient samples and that it is more robust to environmental perturbations than traditional RPA. These features make qRPA potentially useful for at-home testing to monitor the progress of viral infections or other diseases.

Figure 1.

Competitive amplification in RPA can be used to maintain target concentration information. (A) In qRPA, addition of a reference molecule at a known concentration can be used to infer target concentration by measuring the ratio of the target to the reference after amplification. (B) RPA product levels saturate for high input concentrations and are affected by non-specific product formation, depicted by cartoon. (C) In qRPA, although product abundances are still subject to saturation and non-specific products, the ratio is robustly remained and can be used for quantification, depicted by cartoon. (D) Prediction of input concentration by endpoint measurements of RPA and qRPA. qPCR was used to quantify target or reference sequences after amplification by RPA or qRPA. The threshold cycle C_t values (right) were used to calculate a predicted input concentration either by fitting to a standard curve (RPA) or by calculating the target to reference ratio (qRPA). (E) Bland–Altman plot of qRPA outputs. The qRPA data were replotted to show the expected and observed ΔC_t, which indicates the target/reference ratio. Points are plotted against a horizontal line representing an ideal assay which retains ratiometric information perfectly. In each panel, each point depicts the mean of three replicate RPA or qRPA reactions, and error bars depict standard deviation.

Figure 2.

qRPA is robust to certain sequence variations. (A) Measurement of amplification bias from sequence variation. A library with random sequence mismatches in the forward priming region with each linked to internal UMI sequences was synthesized. This input library was amplified using RPA, and then, both input and output libraries were sequenced. (B) Frequency table for reads in the input and output libraries, grouped by number of mismatches in priming sequence. (C) Abundance of library members with a single mismatch in the priming sequence, plotted by mismatch location, with output library abundance normalized by input library abundance.

Figure 3.

qRPA can be combined with a lateral flow assay for fieldable detection. (A) Target and reference amplicons are detected using different hybridization probes and visualized using gold nanoparticles on lateral flow strips in a multiplexed sandwich assay. The relative intensity of target and reference bands can be used to infer target concentration in the sample. (B) Samples were prepared with 1E3 copies of a plasmid carrying a wild-type SARS-CoV-2 N-gene sequence and a varying number of copies of a reference plasmid in which a 28-bp region of the target was replaced with a synthetic barcode. These samples were amplified using qRPA, hybridized with target and reference probes, and visualized on the photographed lateral flow strips. Bands of equal intensity are observed when the target and reference concentrations are equal. (C) RNA was prepared from these plasmids using in vitro transcription, quantified using RT-qRPA, and visualized as above.

Figure 4.

RT-qRPA and lateral flow assays can be used to quantify viral titers in patient samples. (A) Total RNA was extracted from whole blood samples from HIV (+) or (−) patients. Known quantities of in vitro HIV reference RNA containing a synthetic barcode were added to patient samples and amplified in qRPA. The photograph depicts a selection of lateral flow strips used to sort patient samples by viral titer. (B) Remnant nasopharyngeal swab samples from SARS-CoV-2 (+) or (−) patients were tested without extraction. Known quantities of in vitro SARS-CoV-2 reference RNA containing a synthetic barcode were added to patient samples and amplified in qRPA. The photograph depicts a selection of lateral flow strips used to sort patient samples by viral titer.